[mlpack-svn] r13039 - mlpack/trunk/doc/tutorials/emst
fastlab-svn at coffeetalk-1.cc.gatech.edu
fastlab-svn at coffeetalk-1.cc.gatech.edu
Tue Jun 12 20:24:27 EDT 2012
Author: rcurtin
Date: 2012-06-12 20:24:27 -0400 (Tue, 12 Jun 2012)
New Revision: 13039
Modified:
mlpack/trunk/doc/tutorials/emst/emst.txt
Log:
A couple of formatting fixes.
Modified: mlpack/trunk/doc/tutorials/emst/emst.txt
===================================================================
--- mlpack/trunk/doc/tutorials/emst/emst.txt 2012-06-12 20:59:41 UTC (rev 13038)
+++ mlpack/trunk/doc/tutorials/emst/emst.txt 2012-06-13 00:24:27 UTC (rev 13039)
@@ -9,16 +9,16 @@
@section intro_emsttut Introduction
The Euclidean Minimum Spanning Tree problem is widely used in machine learning
-and data mining applications. Given a set \f$S\f$ of points in \f$\mathbb{R}^d\f$,
+and data mining applications. Given a set \f$S\f$ of points in \f$\mathbf{R}^d\f$,
our task is to compute lowest weight spanning tree in the complete graph on \f$S\f$
with edge weights given by the Euclidean distance between points.
Among other applications, the EMST can be used to compute hierarchical clusterings
-of data. A \emph{single-linkage clustering} can be obtained from the EMST by deleting
-all edges longer than a given cluster length. This technique is also referred to as a \emph{Friends-of-Friends} clustering in the astronomy literature.
+of data. A <em>single-linkage clustering</em> can be obtained from the EMST by deleting
+all edges longer than a given cluster length. This technique is also referred to as a <em>Friends-of-Friends</em> clustering in the astronomy literature.
-MLPACK includes an implementation of \emph{Dual-Tree Boruvka} on \f$kd\f$-trees, the empirically and
-theoretically fastest EMST algorithm. For more details, see March, \emph{et al.}, \emph{Euclidean Minimum Spanning Tree: Algorithm, Analysis, and Applications}, in KDD, 2010. An implementation on cover trees is forthcoming.
+MLPACK includes an implementation of <b>Dual-Tree Boruvka</b> on \f$kd\f$-trees, the empirically and
+theoretically fastest EMST algorithm. For more details, see March, <em>et al.</em>, <em>Euclidean Minimum Spanning Tree: Algorithm, Analysis, and Applications</em>, in KDD, 2010. An implementation using cover trees is forthcoming.
\b mlpack provides:
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